Shaip review: a robotics data provider for egocentric capture and manipulation-grade labels

Answer in brief: Shaip is a strong pick when you need new egocentric or demonstration footage plus unusually detailed manipulation and safety labels. That includes grasp pose, contact force, failure-and-recovery grasps, and human-proximity zones referencing ISO 10218 and ISO/TS 15066. It reports 30K+ vetted collectors in 50 cities and 100K+ egocentric and demonstration clips captured. Every engagement starts with scoping and a pilot. Check its SOC 2 status, which is shown inconsistently on its own page.

Top pick for: teaching robots to recover, not just succeed. Every failed grasp is labeled with its category and the corrective action, alongside VLA instruction-action pairs.

Last updated 2026-11-09. This is independent research based on Shaip's own pages. We have not tested the service.

The collection engine: embodiments, scale and delivery

Embodiments. Shaip captures first-person human demonstrations from VR headsets, head-mounted cameras and smartphones, plus multi-sensor capture. In one published program, contributors used head-mounted smartphones running a dedicated app with location verification. We found no public teleoperation offering.

Scale. Shaip reports 30K+ vetted collectors, 50 cities of real-world coverage, 10+ physical AI programs delivered and 1M+ multimodal annotations. It says capture spans 60+ countries and 10 environment types, managed rather than crowdsourced. Its egocentric case study reports 30,000 hours collected and 24,000+ hours annotated across the US and Latin America.

Delivery. Shaip is tool-agnostic and delivers in the formats your pipeline needs, agreed during scoping. Every batch passes multi-layer expert review, and the case study describes one-day review and hand-object visibility checks.

Built for

• Manipulation teams that need grasp-pose, contact and failure/recovery labels.
• Safety teams that need anomaly, collision-risk and human-proximity labels before release.
• VLA teams that need task decomposition, grounding labels and negative examples.

Where Shaip wins

• Label depth. Six specialist domains: VLA, object detection, activity recognition, egocentric, manipulation and grasping, and safety and anomaly.
• Safety-standard aware. Human-proximity zones reference ISO 10218 and ISO/TS 15066.
• Pilot-first. You evaluate the pilot against your own benchmarks before scaling.
• Compliance. ISO 27001, ISO 9001:2015, HIPAA, GDPR, and an NDA signed on day one.

Where it falls short

• The page shows a 'SOC 2 Type II ready' badge but lists SOC 2 Type II as held elsewhere, so ask for the report.
• Scale figures are self-reported, and one case-study figure on Shaip's own page is still marked for verification.
• No teleoperation of your robot is described.

What it costs

Each project is scoped on data type, modality, volume, annotation complexity and QA needs, and usually starts with a paid pilot. See the pricing guide.

Proof points

Shaip's egocentric case study reports 30,000 hours collected and 24,000+ hours annotated and training-ready across the US and Latin America.

Shortlist these instead

• iMerit: managed egocentric capture by full-time staff plus large-scale labeling.
• Appen: calibrated, sensor-synchronized demonstrations in controlled facilities.
• micro1: expert demonstrations of skilled tasks and a robot deployment lab.

Quick answers

Does Shaip collect data or only annotate it?

Both. Shaip runs physical AI data collection (egocentric, demonstration and multi-sensor capture) and can do annotation only or the full collect-and-annotate pipeline.

Is Shaip SOC 2 Type II certified?

Its page is inconsistent: one badge says 'SOC 2 Type II ready', while the compliance section lists SOC 2 Type II. Ask Shaip for the current report.

Can I start with a pilot?

Yes. Shaip scopes a pilot to your requirement so you can evaluate quality against your own benchmarks before scaling.

Sources

• Shaip: Physical AI and robotics data annotation
• Shaip: Egocentric video data collection case study

← Back to the ranked list of the best robotics data providers ·

Named on this page? Join the network for a linked profile, Visit buttons and featured placement.